Centralized restaurant management

ABSTRACT

Described herein is a centralized order computing system that is configured to receive orders from a plurality of sources. The plurality of sources can include delivery applications, remote customer computing devices, and/or service computing devices associated with a merchant. The centralized order computing system may be configured to receive a plurality of orders from the plurality of sources, send the plurality of orders to a kitchen computing system associated with the merchant, receive a notification of order completion, and process the order.

BACKGROUND

Mobile devices are ubiquitous in society today. Typically, mobiledevices contain applications with user interfaces that allow users toconduct various activities on the mobile devices. For instance, amerchant may use a point-of-sale (POS) application on a mobile device,such as a mobile POS device, to engage in transactions with customers atvarious locations. In cases in which the merchant is a restaurant, thetransactions may be orders for food, drinks, and the like. However, theuser interfaces on applications are typically fixed, based on theapplication. For example, a merchant waiter may view the same userinterface when taking an order at a bar or at a table in a dining room.Because of the fixed user interface, a processing time of each order maybe significant due to a need to search through multiple layers of theuser interface to find particular items relevant to the area orcustomer.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items or features.

FIG. 1 illustrates an example environment including a service computingdevice of a POS system configured with a dynamically modifiable userinterface.

FIG. 2 illustrates an example environment with a merchant operating aservice computing device configured with a dynamically modifiable userinterface.

FIG. 3 illustrates an example process of a service computing devicedynamically modifying icons of a user interface based on contextualdata.

FIG. 4 illustrates an example process of a service computing devicedynamically modifying a functionality of a user interface based oncontextual data.

FIG. 5 illustrates an example process of a service computing devicedynamically modifying a theme of a user interface based on contextualdata.

FIG. 6 illustrates a flow diagram of an example process for dynamicallymodifying icons a user interface of a service computing device based oncontextual data.

FIG. 7 illustrates a flow diagram of an example process for dynamicallymodifying a functionality of a user interface of a service computingdevice based on contextual data.

FIG. 8 illustrates a flow diagram of an example process for dynamicallymodifying icons on a user interface of a service computing device basedon a merchant inventory.

FIG. 9 illustrates a flow diagram of an example process for processingan order from a delivery application.

FIG. 10 illustrates select components of an example service computingdevice configured with the dynamically modifiable user interface system.

FIG. 11 illustrates select components of an example base stationcomputing system a POS system may use to process orders from one or moreother computing devices.

DETAILED DESCRIPTION

Some implementations described herein include techniques andarrangements for dynamically modifying a user interface on a computingdevice of a point-of-sale (POS) system based on contextual data. Thecontextual data can include a location of the service computing device(e.g., a point-of-sale (POS) device), a time of day, a day of the week,merchant inventory, merchant preferences, customer preferences, itemsthat are deemed upsell items, items that deemed cross-sell items, a saleand/or special offered by the merchant, and various other contextualfactors corresponding to the use of the computing device.

In various examples, a service computing device can analyze thecontextual data and dynamically modify icons (e.g., text and/or imagescorresponding to selectable items) of the user interface based on one ormore contextual factors. A modification to the icons can includereplacing icons with other icons and/or changing the size, shape, order,image, etc., of various icons. For example, a service computing deviceat a restaurant can determine that a current time corresponds to anadjustment to a lunch menu. Based on the determination, the servicecomputing device can modify the icons on the user interface from iconsassociated with a breakfast menu to icons associated with a lunch menu.

In some examples, the modification to the icons can include anadjustment to a functionality of the user interface. The functionalitycan include one or more functions the user interface is capable ofperforming, such as data input, processing input, determining a statusof previous inputs, automatically uploading data, automaticallydownloading data, and other functions relevant to the particular use ofthe user interface. For example, a computing device located in arestaurant dining area may display icons related to items on a menu, andwhen moved to a kitchen area of the restaurant, the computing device maydisplay order information for multiple tables.

Additionally or alternatively, the computing device can modify a themeof the user interface based on contextual data. The theme can includebackground and/or icon hue (e.g., color and/or shading), backgroundimages, animations, lighting, sounds, and/or other sensory outputs. Forexample, a computing device located in a dimly lit dining area maypresent icons in a dark color on a dimly lit background. However, as thecomputing device is moved toward an outdoor patio area, the computingdevice may dynamically modify the icons to a lighter color, and mayautomatically increase a volume of the computing device.

In various examples, the modification to the user interface can be basedon a location and/or distance of the service computing device relativeto a base station computing device. The base station computing devicecan include a central computing device for one or more service computingdevices. The central computing device can process orders, track customerand/or employee location, track order preparation times, monitorinventory, push updates to the one or more service computing devices,process payments, and/or perform other functions based on theimplementation. For example, a service computing device can receive anorder for a table in a restaurant dining area. After receiving theorder, the waiter can deliver the service computing device to an areawithin a threshold distance of the base station. Based on adetermination that the service computing device is within the thresholddistance of the base station, the user interface on the servicecomputing device can be modified to upload order information to the basestation computing device. The base station computing device can thenprocess the order information with other orders.

The dynamic modification to the user interface can result in a fasterprocessing speed of each input. For example, a relevant menu to aparticular customer can be surfaced automatically based on an indicationof proximity to the particular customer. Due to the automatic surfacingof the relevant menu, the user of the device can quickly and efficientlyinput an order. The increased speed of the order input can result inexcess processing power being available to the service computing deviceto perform other functions. Therefore, the dynamic modification to theuser interface can improve the functioning of the service computingdevice itself.

Additionally or alternatively, the base station computing device caninclude a central computing device for one or more external orderingapplications (e.g., delivery applications, such as food-deliveryapplications). In such examples, the base station computing device canprocess orders, track order preparation times, send order preparationtimes, promotions and/or specials to the external ordering applications,monitor inventory, update menus based on the inventory and/or orderpreparation times, process payments, and perform other functions basedon the implementation. Traditionally, a designated computing device hasbeen required to process information from a particular external orderingapplication. In many instances, the designated computing device isprovided to the merchant from the particular external orderingapplication, to assist in processing orders. The base station computingdevice described herein can provide an improvement to the conventionalprocessing of multiple orders from multiple external orderingapplications by at least centralizing the order system and decreasing anumber of computing devices required to processes the orders.Additionally, the base station computing device can receive the multipleorders and communicate the orders and/or a sequence thereof directly toa preparation computing device, thereby relieving the service computingdevice from processing the orders, and improving the amount ofprocessing power available to the service computing device. The increasein processing power available can result in an increased processingspeed of the service computing device. Thus, the employment of the basestation computing device as the central computing device can include thetechnical benefit of improving the function of the base stationcomputing device and/or the service computing device.

For discussion purposes, example implementations, such as a POS servicecomputing device, are described below with reference to thecorresponding figures. However, implementations herein are not limitedto the POS service computing device. The techniques discussed herein maybe extended to other environments, other system architectures, othertypes of applications, and so forth, as will be apparent to those ofskill in the art in light of the disclosure herein. For example, thetechniques discussed herein may be extended to use in hospitals, retailstores, warehouses, bowling alleys, museums, and/or any otherimplementation which could benefit from a dynamically modifiable userinterface.

FIG. 1 illustrates an example environment 100 including a servicecomputing device 102 (e.g., a point-of-sale (POS) device) of a POSsystem configured with a dynamically modifiable user interface. The POSsystem can include one or more service computing devices 102 and/or abase station computing device 104. The service computing device 102and/or the base station computing device 104 can include any sort ofmobile or non-mobile device operated by a merchant 106 (e.g. owner,employee, contractor, etc.) or a customer of the merchant 106 thatincludes an instance of a user interface modification framework toanalyze contextual data and modify a user interface based on thecontextual data. Contextual data can include a location of the servicecomputing device, a time of day, a day of the week, time of year (e.g.,season), weather, merchant inventory, merchant preferences, customerpreferences, items that are deemed upsell items, items that are deemedcross-sell items, a sale and/or special offered by the merchant, and/orvarious other contextual factors corresponding to the use of the servicecomputing device.

In various examples, the base station computing device 104 can analyzethe contextual data, and can send updates to the service computingdevice 102 as necessary. For example, the base station computing device104 can determine that an inventory of hamburger buns is running low.Based on the determination, the base station computing device 104 cansend an update to the service computing device 102 to de-emphasize(e.g., understate by: adjusting placement on display, adjusting the iconto a smaller size, changing icon colors and/or hue, removing the iconfrom a main page, etc) hamburgers on a menu user interface.

In some examples, the service computing device 102 can analyze thecontextual data and modify the user interface accordingly. For example,the service computing device can determine that a block of timeassociated with a happy hour menu has started (e.g., 4 pm for a happyhour of 4-6 pm, etc.). Based on the determination, the service computingdevice can adjust the user interface to emphasize or highlight (e.g.,adjust placement on display to a higher location, enlarge icon size,adjust icon colors and/or hue, adjust placement of icons in the menu,etc.) the happy hour menu.

In various examples, modifications to the user interface can include anadjustment to one or more icons (e.g., text and/or images correspondingto selectable items) of the user interface. The adjustment to the one ormore icons can include replacing icons with other icons and/or changingthe size, shape, order, image, color, hue, etc., of various icons. Forexample, a service computing device at a restaurant can determine that acurrent time corresponds to an adjustment to a lunch menu. Based on thedetermination, the service computing device can modify the icons on theuser interface from icons associated with a breakfast menu to iconsassociated with a lunch menu. For another example, the service computingdevice at the restaurant can determine that a current day of the weekcorresponds to a menu special, such as Taco Tuesday. Based on thedetermination, the service computing device can modify the userinterface to emphasize (e.g., highlight, etc.) the icons associated withTaco Tuesday items (e.g., tacos, chips and salsa, guacamole, margaritas,etc.).

In some examples, the modifications to the user interface can include anadjustment to a functionality associated with the user interface. Aswill be discussed in further detail below with regard to FIG. 4, thefunctionality can include surfacing different menus, notifications,selectable icons, and the like corresponding to different functions ofthe user interface (e.g., a menu item ordering system, a paymentprocessing system, a recipe display system, a kitchen management system,a seating management system, an order preparation notification system,and the like). For example, a computing device located proximate to atable in a dining area of a restaurant may determine that an orderassociated with the table is complete (e.g., menu items associated withthe order delivered and a pre-determined amount of time has passed sincedelivery to allow for item consumption). Based on the determination oforder completion, the service computing device can automatically adjustthe functionality of the user interface to process payment for theorder, such as by modifying icons from those related to food menu itemsto those related to processing payment.

In some examples, the modifications to the user interface can include anadjustment to a theme associated with user interface. As will bediscussed in further detail below with regard to FIG. 5, the theme caninclude background and/or icon hue (e.g., color and/or shading),background images, animations, lighting, sounds, and/or other sensoryoutputs. For example, a volume in a bar area of a restaurant may begreater than the volume in a dining area of the restaurant. Based on theenvironmental volume increase, the service computing device may increasea volume associated with the user interface upon entering the bar area,to ensure an operator of the service computing device can hear soundsassociated with the user interface.

In various examples, the service computing device 102 can be configuredto modify the user interface based on a location of the servicecomputing device 102. In the illustrative example shown in FIG. 1, amerchant location can include a base station area 106, a dining area108, and a kitchen area 110. In other examples, the merchant locationcan include a greater or lesser number of areas, including sub-sectionsof each area (e.g., dining area 1, dining area 2, table 1, table 2,etc.). For example, a retail store merchant location can include astorage area, a base station area, a shoe department area, a men'sclothing area, a women's clothing area, and the like. Based on adetermination that the service computing device 102 is located in aparticular area, the service computing device 102 can adjust the userinterface accordingly.

In some examples, the service computing device 102 can determine an areaand/or sub-section of the area (e.g., particular location) in which itis located based on data from a sensor of the service computing device102. The sensor can include a camera, a laser scanner, or anothersensor. For example, the service computing device 102 can capture animage at the location via a camera, and can compare the image withstored images at various known locations. Based on a match of the imageto an image of a known location, the service computing device 102 canidentify a current location. For another example, the service computingdevice 102 can scan a code at a particular location via a laser scanner,and can identify the particular location based on the code.

In some examples, the service computing device 102 can determine an areaand/or sub-section of the area in which it is located based on alocation component of the service computing device 102. The locationcomponent can be a global positioning system (GPS) receiver, a beaconand/or components configured to receive beacon signals, a lightdetection and ranging system (LIDAR), a radio detection and rangingsystem (RADAR), a mobile communications triangulation subsystem, and thelike. In various examples, the area and/or sub-section of the area canbe defined by a geographic radius from a position in the area and/orsub-section of the area, a geo-fence around the area and/or sub-sectionof the area, or determining whether the service computing device cancommunicate with another device, such as the base station computingdevice 104, using a specified wireless technology, e.g., Bluetooth® orBluetooth® low energy (BLE).

In some examples, the service computing device 102 can determine that itis located in a sub-section of the area (e.g., in proximity to a Table,such as Table 1) based on a signal from an external location component114, such as a beacon. In such examples, the service computing devicecan receive the signal from the external location component 114, andbased on the signal, determine that the service computing device 102 isproximate to the external location component 114. The determination canbe based on a distance calculation, a signal strength, or other means bywhich the service computing device can determine a proximity to theexternal location component 114.

In various examples, the service computing device 102 may receive one ormore signals from one or more external location components 114. In suchexamples, the service computing device 102 can determine a closestexternal location component 114 to a current location of the servicecomputing device 102. The determination can be based on a comparison ofa distance from each external location component, a ranking of thesignal strength from each external location component, or other means bywhich the service computing device 102 can determine a closest externallocation component.

In some examples, the service computing device 102 can determine an areaand/or a sub-section of the area in which it is located based on asignal from the base station computing device 104. In various examples,the service computing device 102 may receive the signal, and maycalculate a horizontal distance X and/or a vertical distance Y from thebase station computing device 104. In some examples, the base stationcomputing device 104 may calculate the horizontal distance X and/or avertical distance Y, and may provide the distance(s) to the servicecomputing device 102. In some examples, the service computing device 102and/or the base station computing device 104 may determine the areaand/or sub-section of the area in which the service computing device 102is located based on the horizontal distance X and/or a vertical distanceY. For example, the service computing device 102 may determine that thehorizontal distance X and the vertical distance Y is associated with thedining area 110. Based on a determination that the service computingdevice 102 is located in the dining area 110, the service computingdevice may modify the user interface to display icons related to foodand/or beverage menu items. For another example, the service computingdevice 102 may determine that the horizontal distance X and the verticaldistance Y is associated with a particular table, such as Table 1, inthe dining area 108. Based on a determination that the service computingdevice 102 is proximate to Table 1, the service computing device 102 maymodify the user interface to surface icons relevant to Table 1, such asicons related to dessert menu items after the customers located at Table1 have consumed entrées.

In various examples, the service computing device 102 can be configuredto modify the user interface based on merchant inventory. In someexamples, the service computing device 102 can store and track inventorydata, such as in a data store of the service computing device 102. Insome examples, the service computing device can receive inventory datafrom the base station computing device 104. In such examples, the basestation computing device 104 can push updates to the service computingdevice continuously or periodically (e.g., at a certain time each day,every two hours, etc.). In some examples, the base station computingdevice 104 can push an update to the service computing device 102 basedon a determination that a particular item in the inventory has traversed(e.g., crossed over, etc.) an overstock threshold level. A traversal ofan overstock level can include an exceedance of the overstock thresholdlevel or a reduction below the overstock threshold level. The overstockthreshold level may be set by the merchant, such as in merchantpreferences, and/or by the POS system. For example, the servicecomputing device 102 may determine that a particular item isoverstocked. Based on the overstock determination, the service computingdevice 102 may modify the user interface to emphasize the overstockeditem in an attempt to sell more of that item.

In some examples, the base station computing device 104 can push anupdate to the service computing device 102 based on a determination thata particular item in the inventory has traversed an understock thresholdlevel. A traversal of an understock level can include an exceedance ofthe understock threshold level, reaching the understock threshold level(e.g., if the understock threshold level is zero), or a reduction belowthe understock threshold level. The understock threshold level could bezero remaining items, or a limited quantity (e.g., number) of remainingitems, as determined by the merchant 106 and/or the POS system. Forexample, the service computing device 102 may determine that aparticular item is understocked (e.g., a limited amount or noneremaining). Based on the understock determination, the service computingdevice 102 may modify the user interface to de-emphasize (e.g.,understate, etc.) the understocked item in an attempt to discourage thesale of the item.

In various examples, the service computing device 102 can be configuredto modify the user interface based on an attempt to cross-sell an item(e.g., sell a different item than the customer expressed an interestin). In such examples, the service computing device 102 may emphasizethe one or more items to cross-sell on the user interface. In someexamples, a modification based on an attempt to cross-sell can be basedon the inventory, such as if the inventory of an item has decreasedbelow the threshold level.

In various examples, the service computing device 102 can be configuredto modify the user interface based on an attempt to upsell an item. Insuch examples, the merchant 106 can attempt to persuade the customer topurchase something additional or more expensive than another option. Forexample, the service computing device 102 can adjust a size, color,and/or position of an icon to upsell. In some examples, the servicecomputing device 102 can determine what item to attempt to upsell basedon known popular combinations of items. In such examples, the knownpopular combinations can be stored in a data store of the servicecomputing device 102, the base station computing device 104, and/orprovided by the POS system service provider. For example, a customer mayorder a burrito for an entrée. The service computing device 102 mayanalyze the popular combinations and determine that many customers alsoorder chips and salsa with the burrito. Based on the determination of apopular combination, the service computing device may modify the userinterface to display a large icon associated with chips and salsa in thecenter of the user interface.

In some examples, the service computing device 102 can be configured tomodify the user interface based on merchant preferences. The merchantpreferences can be stored in a merchant profile on the service computingdevice 102, the base station computing device 104, and/or a POS systemservice provider device. The merchant preferences can include scheduledsales and/or specials (e.g., happy hour dates and times, food and/orbeverage specials, etc.), user interface adjustments based on time ofday and/or day of week, inventory management information (e.g.,overstock threshold level, understock threshold level, etc.), merchantlocation area information (e.g., specified areas at the merchantlocation, information about external location component 114 signals,etc.), area specific data (e.g., functionality, theme, icons, etc.,associated with each area), employee preferences (e.g., settingsassociated with a particular employee of the merchant operating theservice computing device, such as most commonly sold items by theemployee, handedness of employee, desired font size, etc.), and thelike.

As will be discussed in greater detail below with regard to FIG. 2, theservice computing device 102 can additionally or alternatively beconfigured to modify the user interface based on customer preferences.

FIG. 2 illustrates an example environment 200 with a merchant 202, suchas merchant 106, operating a service computing device 204, such asservice computing device 106, configured with a dynamically modifiableuser interface 206. Although illustrated as being operated by themerchant 202, in some examples, the service computing device 204 mayadditionally or alternatively be operated by a customer. In variousexamples, the user interface 206, such as that discussed above withregard to FIG. 1, can include one or more icons, such as icons 208and/or 210. The one or more icons 208 and/or icons 210 can bemodifiable, such as in size, placement, color and/or hue, image, text,and the like, to emphasize and/or de-emphasize corresponding items.

In the illustrative example, the icon 208(1) is emphasized by the sizeof the icon and placement on the top left corner of the user interface206. As discussed above, the icon 208(1) can be modified (e.g.,emphasized or de-emphasized) based a location of the service computingdevice 204, merchant inventory, merchant preferences, an attempt toupsell, an attempt to cross-sell, a sale and/or special (e.g., adiscount on the corresponding item) offered by the merchant, a time ofday, a day of the week, and/or various other contextual factorscorresponding to the merchant 202 associated with the service computingdevice 204. For example, the merchant 202 may have a Taco Tuesdayspecial from 5 pm-10 pm every Tuesday. The service computing device 204can determine that a current date and time correspond to the TacoTuesday special. Based on the determination that the date and timecorrespond to the special, the service computing device 204 candynamically modify the user interface 206 to emphasize Taco Tuesdayitems, such as icons 208.

In various examples, the icons 208 and icons 210 to be presented can bepre-defined by the merchant, such as in merchant preferences. In someexamples, the icons 208 and icons 210, can be based on known popularitems. In such examples, the known popular items can be determined basedon a merchant transaction history. The merchant transaction history canbe a history of transactions while a sale and/or special is ongoing, ona given day, over a week, a month, and/or over another period of time.In various examples, the merchant transaction history can be a historyof transactions with a particular customer. In some examples, themerchant transaction history can be stored in a data store of theservice computing device 204. In some examples, the merchant transactionhistory can be stored in a base station computing device, and/or a POSsystem service provider computing device, and provided to the servicecomputing device 204.

In some examples, the merchant transaction history can include knownpopular combinations of items (e.g., items that are complementary to oneanother, pair well together, etc.). For example, it can be determinedthat a large quantity (e.g., number) of customers who select icon 208(1)and order tacos also select icon 208(2) and order chips and salsa. Basedon the known combination, the service computing device can modify a sizeand/or placement of the icon 208(2), to emphasize the chips and salsa inan attempt to upsell the customer (e.g., persuade the customer topurchase an additional item). In various examples, based on the knowncombination, the icon 208(2) corresponding to chips and salsa can besurfaced on the user interface 206 responsive to a taco selection viathe icon 208(1) (represented by a bold border surrounding the icon208(1)). In such examples, the icon 208(2) corresponding to thecomplementary item to the item selected can replace one or more othericons 208, or it can be presented as a notification 216 responsive toselection of the icon 208(1).

In various examples, the merchant transaction history can also includepopular alternative food options, presented as icons 210. Using theabove Taco Tuesday example, the transaction history can track purchasesoutside of the Taco Tuesday menu, and determine the most popularalternate food options, illustrated as icons 210. In some examples, thesize and/or shape of the most popular alternate food item may bemodified for emphasis. As an illustrative example, the burgers andsides, displayed as the largest alternate food option icon 210, is themost popular alternate food item, followed by pizza.

Still further, the transaction history may be based on one or more othermerchants utilizing the same payment processing system. For instance,transaction history associated with merchants having similarclassification code and location may be used to determine popular itemsfor a given merchant at a given time of day.

Additionally or alternatively, the merchant transaction history caninclude a status of a current transaction with a particular customer. Invarious examples, the service computing device can determine that theparticular customer is currently on at a second stage of the currenttransaction (e.g., a second course). In some examples, the servicecomputing device 204 can identify an elapsed time since the merchant wasproximate to the particular customer (e.g., a last time the merchantchecked-in at the customer's table). In various examples, based on adetermination that the elapsed time has exceeded a threshold amount oftime (e.g., 10 minutes, 20 minutes, etc.), the service computing device204 can cause a notification 216 to display and remind the merchant tocheck-in with the particular customer. In such examples, the thresholdamount of time may be set based on the status of the currenttransaction. For example, a threshold amount of time set for a customerto consume an entrée may be longer than the threshold amount of time setfor the customer to consume an hors d′oeuvre. The threshold amount oftime could also vary given the actual food item ordered (e.g., steak maylonger to consume than small piece of salmon), size of the party, and/orage profile associated with the customers in the party.

In various examples, the service computing device 204 can modify theuser interface 206 based on customer preferences. In some examples, thecustomer preferences can be stored in a customer profile on the servicecomputing device 204. In other examples, the customer preferences can bestored in a customer profile on a remote device, such as the basestation computing device, the POS system service provider computingdevice, and/or a customer computing device 212, and communicated to theservice computing device via a network. The customer computing device212 can include any type of mobile computing device (e.g., mobilephones, tablet computers, mobile phone tablet hybrids, personal dataassistants (PDAs), laptop computers, media players, personal videorecorders (PVRs), cameras, and any other mobile computers or any othermobile telecommunication devices), embedded devices (e.g., wearablecomputers, implanted computing devices, automotive computers, computernavigation type devices, such as satellite-based navigation systemsincluding global positioning system (GPS) devices and othersatellite-based navigation system devices, appliances, and integratedcomponents for inclusion in a computing device), and/or any other typeof computing device configured to communicate via a network.

The network can include any type of wired and/or wireless network, suchas local area networks (LANs), wide area networks (WANs), personal areanetworks (PANs) (e.g., Bluetooth®, etc.), body area networks (BANs),near field communication (NFC), satellite networks, cable networks,Wi-Fi networks, WiMax networks, mobile communications networks (e.g.,3G, 4G, and so forth) or any combination thereof. The network canutilize communications protocols, including packet-based and/ordatagram-based protocols such as internet protocol (IP), transmissioncontrol protocol (TCP), user datagram protocol (UDP), or other types ofprotocols. Moreover, the network can also include a number of devicesthat facilitate network communications and/or form a hardware basis forthe networks, such as switches, routers, gateways, access points,firewalls, base stations, repeaters, backbone devices, and the like.

In various examples, the service computing device 202 can determine thatit is in proximity to the customer computing device 212 associated witha customer 214. In some examples, the service computing device 204 candetermine a proximity to the customer computing device 212 based on acustomer check-in at a particular location associated with the merchant202. In some examples, the customer check-in can be performedautomatically by an application running on a background of the customercomputing device 204 when the customer computing device 204 is within apredetermined distance of a merchant location, and/or anarea/sub-section of the area associated with the merchant location. Insuch examples, the customer computing device 204 may access a locationcomponent on the device, and determine that the customer 214 has enteredthe merchant location, and/or an area/sub-section of the area associatedwith the merchant location. The customer computing device 204 can thenautomatically send an indication of proximity and/or a check-innotification to the merchant 202, via an automatic check-in. In someexamples, the automatic check-in can also be performed by theapplication running as a background process on the customer computingdevice 212. In some examples, the application running as a backgroundprocess removes the need to run the application on a main thread of theprocessor of the customer computing device 212, thereby savingprocessing speed and increasing efficiency on the main thread of thecustomer computing device 212 processor.

In various examples, the customer check-in can be performed by thecustomer 214 deliberately checking-in via an application on the customercomputing device 212. In some examples, the customer can check-in to theservice computing device 204, such as by inputting a customeridentification code into the service computing device 204 or sending amessage via the network from the customer computing device 212 to theservice computing device 204. For example, the customer 214 can check-inat Table 1 at the merchant location. The service computing device 204can determine that it is within a threshold distance to Table 1, andconsequently within proximity to the customer 214 and/or customercomputing device 212. For another example, a customer 214 could check-into a hospital, and could be placed in a particular room within thehospital. The service computing device 204 could determine a proximityto the customer 214 responsive to crossing a threshold into theparticular room.

In some examples, the service computing device 204 can determine aproximity to the customer computing device 212 based on a signal fromthe customer computing device 212. In such examples, the customercomputing device can emit a signal identifying the customer computingdevice 212. In some examples, the signal may include customer profiledata, such as a code specific to the customer 214. In various examples,the service computing device 204 may determine a proximity based onsignal strength. In some examples, the service computing device 204 maydetermine a proximity based on positioning data embedded in the signal,such as a particular position in an area and/or sub-section of the areaof the merchant location.

In various examples, based on a determination of proximity between theservice computing device 204 and the customer 214 and/or the customercomputing device 212, the service computing device 204 can modify theuser interface 206 according to one or more customer preferences. Insome examples, the customer preferences can be based on a customertransaction history with the merchant In such examples, the customerpreferences can be determined based on commonly purchased items,commonly purchased combinations, etc.

In various examples, the customer preferences can be defined by thecustomer 214. Customer preferences can include favorite items, mostcommonly purchased items, allergies, dietary restrictions (e.g.,vegetarian, vegan, etc.), customer transaction history, desired iconsize (e.g., increased font size for customer with bad eyesight), and thelike. For example, the customer 214 may prefer TexMex food itemsprepared by the merchant 202. As such, the service computing device 204may dynamically modify the restaurant menu to prominently display theTexMex items, such as icons 208. Using the hospital example above, thecustomer 214 may have a severe allergy to penicillin. Based on theallergy, the service computing device 204 can prominently display in alarge icon, similar to icon 208(1), the allergy, to ensure penicillin isnot administered to the patient.

In various examples, one or more icons corresponding to customerpreferences can be emphasized on the user interface 206. In suchexamples, the emphasis can include a different size, shape, color and/orhue of the icon as compared to other icons. In the illustrative example,icon 208(3) represents a peanut allergy of the customer, emphasized by adifferent color than the other icons 208 and 210.

In some examples, the customer preferences can include preferredconversation topics. In such examples, the merchant 202 may be able torefer to the icon 208(4) to facilitate a conversation between themerchant and the customer 214, thereby enhancing the customer's overallexperience with the merchant In some examples, the icon 208(4) and/oranother icon 208 or icon 210 may include customer information, such as acustomer name, birthday, and the like. In such examples, the merchant202 may access the customer's information, and refer to the customer byname, further enhancing the customer's overall experience with themerchant In various examples, the icon 208(4) and/or another icon 208 oricon 210 can include previously submitted feedback regarding thecustomer's experience. In such examples, the merchant 202 may be able toaccess and address the feedback with the customer 214, to furtherenhance the customer experience.

In some examples, based on a determination of proximity between theservice computing device 204 and the customer 214 and/or the customercomputing device 212, the service computing device 204 can modify theuser interface 206 according to a current ongoing transaction (e.g., aparticular meal the customer is consuming, etc.). In such examples, theservice computing device 204 can determine that the customer 214 hascompleted a first stage of the ongoing transaction, and can modify oneor more icons to reflect items for a second stage of the ongoingtransaction. For example, the service computing device 204 can determinethat the customer has consumed an entrée. The determination that theentrée has been consumed can be based on a pre-determined amount of timethat has passed since the entrée was ready for delivery and/or deliveredto the customer. Based on the determination of entrée consumption andproximity to the particular customer, the service computing device 204can dynamically modify icons 208 and/or icons 210 to icons correspondingto dessert menu items.

FIG. 3 illustrates an example process of an example service computingdevice 300, such as service computing device 102 and 204, dynamicallymodifying icons 302 of a user interface 304, such as user interface 206,based on contextual data. Contextual data can include a location of theservice computing device 300, a time of day, a day of the week, time ofyear (e.g., season), weather, merchant inventory, merchant preferences,customer preferences, items that are deemed upsell items, items that aredeemed cross-sell items, a sale and/or special offered by the merchant,and various other contextual factors corresponding to the use of theservice computing device 300.

At 306, the service computing device 300 determines first contextualdata and displays first icons 302(1) based on the contextual data. Thefirst contextual data can be determined based on an analysis of one ormore factors corresponding to the use of the service computing device300. In the illustrative example, the analysis can include adetermination that a time of day corresponds to a breakfast menu. Basedon this determination, the service computing device 300 can display afirst set of icons 302(1) corresponding to the breakfast menu. In someexamples, the analysis can include an analysis of customer preferences,and a determination that the customer prefers particular menu items,such as the breakfast menu.

In various examples, the analysis can include a determination toemphasize one or more items. The emphasis can be presented by increasinga size, shape, color and/or hue of the icon 302, changing a placement ofthe icon 302, or any other adjustments to make the icon 302 stand out onthe display. The emphasis can be based on merchant inventory, currentweather, an attempt to upsell an item, an attempt to cross-sell an item,sales and/or specials offered by the merchant, transaction history ofthe merchant (e.g., known popular items sold at a time of day, a day ofthe week, time of year (e.g., season), known popular combinations ofitems sold, etc.

In some examples, the analysis can include a determination tode-emphasize one or more items. A de-emphasis of an item can be based onmerchant inventory, current weather, an attempt to cross-sell, and/orother factors in which the merchant may discourage the sale of aparticular item. The de-emphasis can be presented by removing the icon302 corresponding to the one or more items from the display page. Invarious examples, the user interface 304 can include multiple displaypages. In some examples, the de-emphasis can be presented by includingthe icon corresponding to the one or more items on a display page otherthan a main display page. For example, the de-emphasis can includepresenting the icon on a last page of the multiple display pages.

In various examples, the service computing device 300 can dynamicallydetermine to emphasize and/or de-emphasize one or more items based oncontextual factors. For example, if a customer orders the last muffin,the service computing device 300 can dynamically modify the userinterface 304 by removing the muffin icon from the user interface, andreplace it with a pastry icon.

At 308, the service computing device 300 determines second contextualdata and displays second icons 302(2) based on the contextual data. Invarious examples, the second contextual data can include a change in thetime of day from a time corresponding to the breakfast menu to a timecorresponding to a lunch menu. In some examples, the second contextualdata can include a determination of an event nearby the merchantlocation, or displayed on a screen at the merchant location, which couldaffect menu items most likely to be ordered by customers. In suchexamples, the service computing device 300 could dynamically modify theicons 302(1) to a second set of icons 302(2) to cater to the customerpreferences or external environment (e.g., cold/hot day recommendhot/cold beverage items). For example, a merchant may typically adjustfrom a breakfast to a lunch menu at 11 am. However, the servicecomputing device 300 may determine that a football game starts at 10 am,and during football games, the customers prefer to consume items on thelunch menu. Accordingly, the service computing device 300 may adjust oneor more of the icons 302 to those corresponding to lunch menu items.

In some examples, the service computing device 300 may determine that anevent is taking place nearby the merchant or will be presented on adisplay screen at the merchant location, and may generate one or moresales and/or specials (e.g., discounts, etc.) based on the event. Insuch examples, the service computing device 300 can emphasize the icons302 corresponding to the one or more specials. For example, the merchantmay offer hamburgers and alcoholic beverages on special during theevent. Accordingly, the service computing device 300 can modify theicons corresponding to the hamburgers and alcoholic beverages to makethem stand out. Additionally or alternatively, the service computingdevice may display a notification 310 that the particular items areoffered at a discounted price to further incentivize the purchase.

FIG. 4 example process of an example service computing device 400, suchas service computing device 300, dynamically modifying a functionalityof a user interface 402, such as user interface 304, based on contextualdata (e.g., one or more contextual factors). A functionality can includeone or more functions the user interface 402 is capable of performing,such as data input (e.g., order entry, etc.), data display (e.g., recipedisplay, discount notifications, order status notifications, etc.),status of previous inputs (e.g., order management, order status, etc.),data processing (e.g., payment processing, order processing, ordersequencing, etc.), automatically uploading data (e.g., from a basestation computing device based on a determination of proximity (e.g.,order upload in order processing system, etc.), from a customercomputing device based on a determination of proximity (e.g., uploadingcustomer preference data, etc.)), automatically downloading data (e.g.,to a base station computing device based on a determination ofproximity, to a customer computing device based on a determination ofproximity), and/or other functions relevant to the particular use of theuser interface 402. In various examples, the modification to thefunctionality can be illustrated as a modification to the icons 404corresponding to the functionality. In such examples, the modificationto the functionality can include surfacing icons 404 related to thefunctionality, surfacing notifications 406 relevant to thefunctionality, and the like.

At 408, the service computing device 400 can determine first contextualdata and display icons 404(1) corresponding to a first functionality. Invarious examples, the first contextual data can include a location ofthe service computing device. The location can be a merchant location,an area and/or a sub-section of an area of the merchant location. Invarious examples, the location can be determined by one or more sensorsof the service computing device 400. In some examples, the location canbe determined by a location component of the service computing device400. The location component can be a global positioning system (GPS)receiver, a beacon and/or components configured to receive beaconsignals, a light detection and ranging system (LIDAR), a radio detectionand ranging system (RADAR), a mobile communications triangulationsubsystem, and the like. In various examples, the area and/orsub-section of the area can be defined by a geographic radius from aposition in the area and/or sub-section of the area, a geo-fence aroundthe area and/or sub-section of the area, or determining whether theservice computing device can communicate with another device, such asthe base station computing device, using a specified wirelesstechnology, e.g., Bluetooth® or Bluetooth® low energy (BLE).

In some examples, the service computing device 400 can determine that itis located in a sub-section of the area (e.g., in proximity to a Table,such as Tables 1-5) based on a signal from an external locationcomponent, such as a beacon. In such examples, the service computingdevice 400 can receive the signal from the external location component,and based on the signal, determine that the service computing device 400is proximate to the external location component. The determination canbe based on a distance calculation, a signal strength, or other means bywhich the service computing device can determine a proximity to theexternal location component.

In various examples, the service computing device 400 can determine thatit is in proximity to a customer computing device associated with acustomer. In some examples, the service computing device 400 candetermine a proximity to the customer computing device based on acustomer check-in at a particular location associated with the merchantIn some examples, the customer check-in can be performed automaticallyby an application running on a background of the customer computingdevice when the customer computing device 204 is within a predetermineddistance of a merchant location, and/or an area/sub-section of the areaassociated with the merchant location. In such examples, the customercomputing device determines that it has entered the merchant location,and/or an area/sub-section of the area associated with the merchantlocation based on a location component. The customer computing devicecan then automatically send an indication of proximity and/or a check-innotification to the merchant, via an automatic check-in. In someexamples, the automatic check-in can also be performed by theapplication running as a background process on the customer computingdevice. In some examples, the application running as a backgroundprocess removes the need to run the application on a main thread of theprocessor of the customer computing device, thereby saving processingpower and/or speed, and increasing efficiency on the main thread of thecustomer computing device processor.

In various examples, the customer check-in can be performed by thecustomer deliberately checking-in via an application on the customercomputing device. For example, the customer can check-in at Table 1 atthe merchant location. The service computing device 400 can determinethat it is within a threshold distance to Table 1, and consequentlywithin proximity to the customer and/or customer computing device. Foranother example, a customer can check-in to a hospital, and be placed ina particular room within the hospital. The service computing device 400can determine a proximity to the customer responsive to crossing athreshold into the particular room.

In some examples, the service computing device 400 can determine aproximity to the customer computing device based on a signal from thecustomer computing device. In such examples, the customer computingdevice can emit a signal identifying the customer computing device. Insome examples, the signal may include customer profile data, such as acode specific to the customer. In various examples, the servicecomputing device may determine a proximity based on signal strength. Insome examples, the service computing device 400 may determine aproximity based on positioning data embedded in the signal, such as aparticular position in an area and/or sub-section of the area of themerchant location.

In various examples, based on a determination of proximity between theservice computing device 400 and the customer computing device, theservice computing device 400 can display icons 404 corresponding to afirst functionality, based on one or more customer preferences. In someexamples, the customer preferences can be based on a customertransaction history with the merchant In such examples, the customerpreferences can be determined based on commonly purchased items,commonly purchased combinations, previously used payment instrumentinformation, etc. For example, the service computing device 400 maydetermine a proximity to a particular customer corresponding to acustomer profile. The service computing device 400 may access thecustomer preferences in the customer profile and determine that thecustomer prefers to order alcoholic beverages from the merchant Based onthe determination of the customer preferences, the service computingdevice 400 may display icons corresponding to a bar menu functionality,including instructions on how to mix particular beverages.

In some examples, the customer preferences can be defined by thecustomer. In such examples, the customer can input one or morepreferences into a customer profile. For example, the customer can inputpreferred payment instrument information, to allow for automatic paymentprocessing.

In various examples, the first contextual data can include a status of aparticular customer and/or a customer in a particular area and/orsub-section of the area. The status of the customer can include an orderhistory (e.g., what the customer has ordered, consumed, etc.),completion of a transaction (e.g., the particular customer has paid forthe meal, etc.), and the like. In various examples, the servicecomputing device 400 can first determine that it is located proximate toa particular sub-section. Responsive to the location determination, theservice computing device 400 can display icons corresponding to a firstfunctionality based on the customer status at the particular location.For example, the service computing device 400 can determine that it isproximate to Table 1 and the customer at Table 1 has consumed theordered items (e.g., a predetermined period of time has passed sinceorder delivery). Based on the determination of the contextual factors oflocation and customer status, the service computing device 400 canautomatically and dynamically modify the functionality of the userinterface 402 to display icons corresponding to a bill for the customerand/or process payment for the bill. In examples in which the servicecomputing device 400 identifies a proximity to a customer associatedwith a customer profile, the service computing device 400 canautomatically process payment based on stored payment instrumentinformation, and display icons corresponding to the processed payment.In such examples, the service computing device 400 can provide aseamless payment experience for the customer, and improve an overallexperience between the customer and the merchant.

In various examples, the first functionality can include the function ofdisplaying notifications 406 relevant to the first contextual data. Inthe illustrative example, the first contextual data includes a locationof the service computing device in a dining area of a restaurant, suchas dining area 110. The first functionality, therefore, can include adisplay of a menu of selectable icons 404(1), to enable the merchant totake an order from a table. As illustrated, the service computing device400 may receive a notification from the kitchen including an indicationthat a particular order is ready for pick-up. Based on the indication,the merchant can adjust a next action, and retrieve the order from thekitchen to deliver to the table.

In some examples, the user interface 402 can be configured to processand display notifications when operating in multiple functionalities. Insuch examples, the user interface 402 can alert the merchant ofimportant information regardless of the current contextual data and/orcurrent task being performed by the merchant.

In various examples, the first contextual data can include a currenttime component. The time component can include a time of day, a day ofthe week, a month of the year, a season, or other time-based component.In such examples, the service computing device can determine the timecomponent, and adjust the functionality of the user interface based atleast in part on the time component. In some examples, the timecomponent may be pre-defined, such as in merchant preferences stored ina merchant profile. For example, a particular merchant may pre-define akitchen closing time as 10 pm. Based on a determination that the time is10 pm, the service computing device 400 may adjust the functionality ofthe user interface 402 to display and process the bar menu, regardlessof a location of the service computing device in the restaurant.

At 410, the service computing device 400 can determine second contextualdata and dynamically modify icons 404 based on a second functionalitycorresponding to the second contextual data. The second contextual data,similar to the first contextual data, can be based on a location of theservice computing device 400, a status of a customer at a particularlocation, a proximity to a particular customer, and/or other contextualfactors related to the functionality of the service computing device400.

In the illustrative example, the second contextual data includes alocation of the service computing device in a kitchen area of therestaurant. Responsive to a location determination, the servicecomputing device 400 can modify icons 404 from the dining area icons404(1) to the kitchen area icons 404(2), based on the secondfunctionality.

In various examples, the second contextual data can include a thresholdamount of time (e.g., 5 seconds, 10 seconds, 1 minute, etc.) the servicecomputing device 400 is located in an area and/or a sub-section of thearea. In such examples, the service computing device 400 determines thatthe threshold time has been exceeded prior to modifying the icons 404 tothose corresponding to the second functionality. For example, a merchantcarrying a service computing device 400 into the kitchen area to quicklyretrieve an order may not exceed the threshold time required to modifythe icons 404.

In various examples, the first and/or second functionality can includeone or more icons 404(2A)-404(2D) that are selectable, non-selectable,or include selectable components. For example, icons 404(2A) and 404(2B)include non-selectable icons 404, informing the merchant that particularorders are ready to be delivered to particular tables. For anotherexample, icon 404(2D), includes a selectable component 412. In someexamples, the selectable component 412 can include a notification 406setting. In the illustrative example, the second functionality caninclude an estimated time in which a particular order will be ready.Based on the estimated time, the icons 404(2) can be modified to includea reminder notification query. In some examples, the remindernotification query can be presented based on the estimated timeexceeding a threshold (e.g., 5 minutes, 10 minutes, 15 minutes, etc.).As illustrated, the merchant can receive a notification 406 from thekitchen responsive to answering the reminder notification query of theselectable component 412 in the affirmative.

FIG. 5 illustrates an example process of a service computing device 500,such as service computing device 400, dynamically modifying a theme 502of a user interface 504, such as user interface 402, based on contextualdata (e.g., one or more contextual factors). The theme 502 can includebackground and/or icon hue (e.g., color and/or shading), backgroundimages, animations, lighting, sounds, and/or other sensory outputs.

In various examples, the contextual data can include a location of theservice computing device 500. As discussed above, the service computingdevice 500 can determine that it is located in an area and/or asub-section of the area (e.g., in proximity to a Table, such as Table 1)based on data from one or more sensors, an internal location componentand/or an external location component.

In some examples, the contextual data can include proximity to aparticular customer. In such examples, the service computing device 500can determine that it is within a threshold distance of the customerbased on a customer check-in to an area and/or sub-section of the areaassociated with the merchant, a signal received from a customercomputing device, and/or other ways of determining proximity betweendevices. In various examples, based on a determination of proximity to aparticular customer, the service computing device can modify a theme 502based on customer information and/or customer preferences. In suchexamples, the customer information and/or customer preferences can bestored in the customer profile. The customer information and/or customerpreferences can include customer name, birthday, handedness (e.g.,right-handed or left-handed), hobbies, preferred seasons, preferredholidays, preferred sports teams, meal preferences, and otherinformation pertinent to the customer. For example, a customer canupdate a profile to reflect that the customer is a Mariners fan. Basedon the update and a determination that the customer and the servicecomputing device are in proximity to one another, the service computingdevice 500 can present a Mariners theme 502 on the user interface 504.

In some examples, the contextual data can include a time component. Thetime component can include a time of day, a day of the week, time ofyear (e.g., season), a holiday period, and the like. In variousexamples, the service computing device 500 can determine the timecomponent, and present a theme 502 on the user interface 504 based atleast in part on the time component. In some examples, the timecomponent may be pre-defined, such as in merchant preferences stored ina merchant profile. For example, a particular merchant may include apreference to present snowflakes on the background of the user interface504 during the winter. Based on a determination that the current seasonis winter, the service computing device 500 may adjust the theme 502 toinclude snowflakes in the background.

In some examples, the contextual data can include environmental factors.The environmental factors can include lighting, weather, volume, etc. Invarious examples, the service computing device 500 can user one or moresensors (e.g., light sensor, volume sensor, etc.) to determine theenvironmental factors. In such examples, based on the environmentalfactors, the service computing device 500 can present a particular theme502. For example, in a dimly lit area, the service computing device 500may adjust a background of the user interface 504 to a darker color. Foranother example, in a loud area, the service computing device 500 mayincrease a volume of the user interface 504.

At 506, the service computing device 500 can determine first contextualdata and can present a corresponding theme 502. In the illustrativeexample, the first contextual data can include a location in a dimly litdining room. Based on the first contextual data, the service computingdevice 500 can present theme 502(1) including an image 508(1)corresponding to the dining room, and dark colors for the user interface504 and icon backgrounds corresponding to the area lighting.

At 510, the service computing device 500 can determine second contextualdata and can dynamically modify the theme 502 based on the secondcontextual data. In the illustrative example, the second contextual dataincludes a location in a brightly lit patio. Based on the secondcontextual data, the service computing device 500 can present theme502(2), including an image 508(2) corresponding to the patio, and brightcolors for the user interface 504 and icon backgrounds corresponding tothe brightly lit area.

FIGS. 6-9 illustrate flow diagrams of processes for generatingmulti-merchant loyalty programs and enrolling customers therein.Processes 600, 700, 800, and 900 are illustrated as collections ofblocks in logical flow diagrams, which represent a sequence ofoperations, some or all of which can be implemented in hardware,software or a combination thereof. In the context of software, theblocks may represent computer-executable instructions stored on one ormore computer-readable media that, when executed by one or moreprocessors, program the processors to perform the recited operations.Generally, computer-executable instructions include routines, programs,objects, components, data structures and the like that performparticular functions or implement particular data types. The order inwhich the blocks are described should not be construed as a limitation.Any number of the described blocks can be combined in any order and/orin parallel to implement the process, or alternative processes, and notall of the blocks need be executed. For discussion purposes, theprocesses are described with reference to the environments,architectures and systems described in the examples herein, although theprocesses may be implemented in a wide variety of other environments,architectures and systems.

FIG. 6 illustrates a flow diagram of an example process 600 fordynamically modifying icons on a user interface of a service computingdevice based on contextual data.

At 602, the service computing device can present icons on the userinterface of a service computing device. In some examples, the icons caninclude selectable representations of items provided and/or offered by amerchant via the user interface. In various examples, the icons cancorrespond to a functionality of the user interface. For example, a userinterface can be used to manage a seating chart in a restaurant. Theicons can thus correspond to different tables in a dining area. Foranother example, the user interface can be used to process orders in arestaurant. The icons can thus correspond to selectable menu items.

In various examples, the icons and/or the size, shape, color, hue,placement, etc., thereof can be determined based on an initial settingof the service computing device. For example, a merchant can turn theservice computing device on, and the service computing device canpresent a standard menu display with equally sized icons orderedalphabetically.

At 604, the service computing device can analyze contextual data of theservice computing device. The contextual data can include a location ofthe service computing device, a time component (e.g., a time of day, aday of the week, time of year (e.g., season)), weather, merchantinventory, merchant preferences, customer preferences, items that aredeemed upsell items, items that are deemed cross-sell items, a saleand/or special offered by the merchant, and/or various other contextualfactors corresponding to the use of the service computing device.

In various examples, the service computing device can receive contextualdata from a remote computing device, such as a base station computingdevice and/or a POS system service provider. For example, the servicecomputing device can receive merchant preferences from a base stationcomputing device, and can determine the icons to present based on themerchant preferences.

At 606, the service computing device can dynamically modify one or moreicons based on the contextual data. In various examples, a modificationto the one or more icons can include replacing an icon with another iconand/or changing the size, shape, order, image, color, hue, placement,etc., of an icon (e.g., adjusting a visual appearance of the icon). Forexample, a service computing device at a restaurant can determine that acurrent time corresponds to an adjustment to a lunch menu. Based on thedetermination, the service computing device can modify the icons on theuser interface from icons associated with a breakfast menu to iconsassociated with a lunch menu. For another example, the service computingdevice at the restaurant can determine that a current day of the weekcorresponds to a menu special, such as Thirsty Thursday. Based on thedetermination that it is Thirsty Thursday, the service computing devicecan modify the user interface to emphasize the icons associated withThirsty Thursday items (e.g., discounted beer, rum, tequila, whiskey,etc.).

In various examples, the modifications to the one or more icons caninclude an adjustment to a functionality associated with the userinterface. The functionality can include surfacing different menus,notifications, selectable icons, and the like. In some examples, themodifications to the one or more icons can include an adjustment to atheme associated with user interface. The theme can include backgroundand/or icon hue (e.g., color and/or shading), icon animation, backgroundlighting, sounds, and/or other sensory outputs.

FIG. 7 illustrates a flow diagram of an example process 700 fordynamically modifying a functionality of a user interface of a servicecomputing device based on contextual data.

At 702, the service computing device can determine a first location. Invarious examples, the first location can be determined based on alocation component of the service computing device. In some examples,the first location can include a location relative to a base stationcomputing device. In such examples, the first location can be a distancefrom a base station computing device of a point-of-sale (POS) system,such as a two-dimensional distance (e.g., X/Y distance) from the basestation computing device. In some examples, the first location caninclude an area and/or a sub-section of an area corresponding to amerchant location.

In various examples, the service computing device can also determine oneor more contextual factors associated with a use of the servicecomputing device. The one or more contextual factors can include a timeof day, a day of the week, time of year (e.g., season), weather,merchant inventory, merchant preferences, customer preferences, itemsthat are deemed upsell items, items that are deemed cross-sell items, asale and/or special offered by the merchant, and/or various othercontextual factors corresponding to the use of the service computingdevice.

In various examples, the service computing device can receive the one ormore contextual factors from a remote computing device, such as a basestation computing device and/or a POS system service provider.

At 704, the service computing device can present icons corresponding toa first functionality on a user interface of a service computing device.The functionality can include one or more functions or capabilities ofthe service computing device at the first location and/or at a giventime. For example, for a service computing device in a restaurant, thefunctions can include surfacing menus, displaying notifications,receiving orders, processing payment, managing customer flow at tables,managing a kitchen ordering system, automatically uploading data,automatically downloading data, and the like.

At 706, the service computing device can determine a second location. Invarious examples, the first location can be determined based on alocation component of the service computing device. In some examples,the second location can include a location relative to a base stationcomputing device. In such examples, the second location can be adistance from a base station computing device of a point-of-sale (POS)system, such as a two-dimensional distance (e.g., X/Y distance) from thebase station computing device. In some examples, the second location caninclude an area and/or a sub-section of an area corresponding to amerchant location.

In various examples, the service computing device can also determine oneor more contextual factors associated with a use of the servicecomputing device. The one or more contextual factors can include a timeof day, a day of the week, time of year (e.g., season), weather,merchant inventory, merchant preferences, customer preferences, itemsthat are deemed upsell items, items that are deemed cross-sell items, asale and/or special offered by the merchant, and/or various othercontextual factors corresponding to the use of the service computingdevice.

In various examples, the service computing device can receive the one ormore contextual factors from a remote computing device, such as a basestation computing device and/or a POS system service provider.

At 708, the service computing device can identify a second functionalitybased on the second location. The second functionality can include oneor more functions or capabilities of the service computing devicerelevant to the context of use. In various examples, the secondfunctionality can also be based, at least in part, on the one or morecontextual factors.

At 710, the service computing device can dynamically modify one or moreicons of the user interface based on the second functionality. Amodification to the one or more icons can include replacing an icon withanother icon and/or changing the size, shape, order, image, color, hue,placement, etc. of an icon. For example, a service computing device at arestaurant can be relocated from a host station with a firstfunctionality of managing a seating chart, to a dining area with asecond functionality of receiving orders from customers. Based on therecognition of the change in contextual data and consequentlyfunctionality, the service computing device may modify the icons todisplay icons corresponding to a restaurant menu.

FIG. 8 illustrates a flow diagram of an example process 800 fordynamically modifying icons on a user interface of a service computingdevice based on a merchant inventory.

At 802, the service computing device can determine a contextcorresponding to the use of the device. In various examples, the contextcan include one or more contextual factors, such as a location of theservice computing device, a time component (e.g., a time of day, a dayof the week, time of year (e.g., season)), weather, merchant inventory,merchant preferences, customer preferences, items that are deemed upsellitems, items that are deemed cross-sell items, a sale and/or specialoffered by the merchant, and/or various other contextual factorscorresponding to the use of the service computing device.

In various examples, the service computing device can receive contextualdata from a remote computing device, such as a base station computingdevice and/or a POS system service provider. For example, the servicecomputing device can receive merchant preferences from a base stationcomputing device, and can determine the icons to present based on themerchant preferences.

At 804, the service computing device can present a set of icons in anorder based at least in part on the context. In some examples, the iconscan include selectable representations of items provided and/or offeredby a merchant via the user interface. In various examples, the icons cancorrespond to a functionality of the user interface. For example, a userinterface can be used to manage a seating chart in a restaurant. Theicons can thus correspond to different tables in a dining area. Foranother example, the user interface can be used to process orders in arestaurant. The icons can thus correspond to selectable menu items.

In various examples, the icons and/or the size, shape, color, hue,placement, etc., thereof can be determined based on an initial settingof the service computing device. For example, a merchant can turn theservice computing device on, and the service computing device canpresent a standard menu display with equally sized icons orderedalphabetically.

At 806, the service computing device can analyze an inventory associatedwith the merchant. An analysis of the inventory can include adetermination of a quantity (e.g., number) of each item in the inventorythat is available, a determination of icons associated with each item(e.g., menu item #13 includes items A, B, and C, menu item #26 includesitems D and E, etc.). In various examples, the inventory can include athreshold overstock number and/or a threshold understock number for eachitem in the inventory. In some examples, based on the quantity of anitem depleting below the threshold understock number, the servicecomputing device can order the item from an item supplier. In variousexamples, the service computing device can send a notification of theitem depletion to a centralized computing system, such as a base stationcomputing device. In such examples, the service computing device cancause the centralized computing system to order the item from thesupplier.

In various examples, the service computing device can receive inventorydata from a remote computing device, such as a base station computingdevice and/or a POS system service provider. For example, the basestation computing device can include a centralized order hub andinventory management system. The base station computing device can tracka quantity of each item in the inventory, and can send updates to theservice computing device as necessary. The updates can be continuous,periodic, or situationally dependent, and can determine the icons topresent based on the merchant preferences.

In some examples, the service computing device can send the remotecomputing device order information. In such examples, the remotecomputing system can process the order, analyze the inventory based onthe order, and send inventory information to the service computingdevice.

At 808, the service computing device can dynamically modify the set oficons based at least in part on the inventory. In various examples, theservice computing device can process orders and determine an overstockor understock of a particular item of inventory. In some examples, theservice computing device can receive inventory information, such as anitem overstock or understock, from a remote computing device, such asthe base station computing device.

In various examples, the service computing device can determine anoverstock of an item of inventory. In such examples, the servicecomputing device can dynamically modify an icon associated with theoverstocked item, to emphasize the item and encourage a sale. Theemphasis can include increasing a size, shape, color, hue, placement,and the like, of the icon, presenting a notification of a discount, etc.

In some examples, the service computing device can determine anunderstock of an item of inventory. In such examples, the servicecomputing device can dynamically modify an icon associated with theunderstocked item, to de-emphasize the item and discourage a sale. Thede-emphasis can include removing the icon from a user interface,removing the icon from a main page of the user interface, replacing theicon with an icon corresponding to another item that is substantiallysimilar, and other ways to discourage the sale of an item.

In some examples, the service computing device can modify the set oficons based on one or more contextual factors, such as a location of theservice computing device, a merchant preference, a customer preference,a time component, a merchant transaction history, a customer transactionhistory, a sale or special for an item, and the like. For example, theservice computing device can identify a customer and access atransaction history associated with the customer. The service computingdevice can determine, from the transaction history, that a customercommonly purchases a particular item. The service computing device canidentify one or more substantially similar items to the particular item,and can emphasize the icons corresponding to the substantially similaritems (e.g., adjust the size, shape, placement, color, hue, etc.) toencourage a sale of one or more of the substantially similar items. Insome examples, the identification of the substantially similar items canbe based on a low quantity (e.g., an understock) of the particular itemin the inventory.

The dynamic modification of the user interface based on an analysis ofthe inventory can improve a functioning of the service computing device.The improvements can include decreasing a number of inputs required toprocess each order, thereby increasing a processing speed of the servicecomputing device, rendering the service computing device more efficient.Additionally, the inventory analysis described herein can improve thetechnology and/or technical field of inventory supply management. Invarious examples, the service computing device can continually and/orperiodically update the inventory with the processing of each order(e.g., update a data structure, database, etc. associated with theinventory). In such examples, the inventory supply management system isgreatly improved because the system can determine, in substantiallyreal-time, what the inventory for a particular item is. Accordingly, theinventory supply management system can quickly determine an overstocksituation, an understock situation, and/or one or more items to includein an order from a supplier.

FIG. 9 illustrates a flow diagram of an example process 900 forprocessing an order from a remote delivery application.

At 902, the computing device can receive an order from a deliveryapplication. In some example, the computing device can receive one ormore delivery applications and/or one or more remote computing devices.

At 904, the computing device can determine a time associated with theorder. In various examples, the time can be a preparation timeassociated with the order. In such examples, the time can be a longesttime required to prepare an item in the order. The time can bedetermined based on a quantity (e.g., number) of employees working inthe kitchen, a particular employee working in the kitchen, an upcomingshift change in the kitchen, a cooking time for the items in the order,an ingredient preparation time for items in the order, and other factorsaffecting a preparation time associated with the order. In variousexamples, the preparation time can be based on a pre-determined timestored in the computing device for a particular item in the order. Insuch examples, the computing device can include a list of menu items andassociated preparation times.

In some examples, the computing device can determine a time associatedwith each item in the order. In such examples, the computing device cansequence the items of the order individually, to coordinate thecompletion of each item in the order to be at substantially the sametime.

In various examples, the time can be associated with one or more factorsexternal to the merchant operation. The one or more factors can includeweather, traffic (e.g., in proximity to a merchant location, between thecustomer and the merchant location, etc.), courier availability, otherpending order pick-ups or deliveries of the courier, and other factorsaffecting a time in which a courier may arrive at the merchant location.

At 906, the computing device can send the order to a kitchen computingsystem (e.g., kitchen display system). In some examples, the order canbe sequenced with one or more other orders and/or one or more items ofthe order and/or one or more other orders.

In various examples, the computing device can receive an indication fromthe kitchen computing system that there is a delay in processing theorder. The indication can be based on a staffing in the kitchen beingbelow a pre-defined minimum quantity (e.g., number) of employees (e.g.,a threshold minimum quantity), a pending shift change, a particularemployee working in the kitchen, a training evolution, an increase inorders received from the dining room, or other factors that may affect apreparation time of an order. In some examples, the computing system cancalculate an updated time associated with the order based on theindication. In various examples, the computing system can send theupdated time to the respective delivery application. In some examples,the updated time may be sent to the respective delivery applicationbased on a determination that a difference between the time and theupdated time exceeds a threshold amount of time (e.g., 5 minutes, 7minutes, 10 minutes, etc.).

In some examples, responsive to receiving the indication that there is adelay in processing the order, the computing device can send anotification to a manager of the merchant In such examples, thenotification can include details regarding the delay, a request toaddress a cause of the delay, a solution to the cause of the delay(e.g., more employees needed in the kitchen, etc.), and the like. Forexample, the notification to the manager can include a delay inprocessing the order based on training currently happening in thekitchen. The notification can include a suggestion to terminate thetraining early, to allow one or more employees to direct full attentionto processing orders.

At 908, the computing device can receive a notification of completion ofthe order from the kitchen computing system. In some examples, thecomputing device can send the notification of order completion to thedelivery application and/or the remote computing device. In suchexamples, the delivery application and/or the remote computing devicecan notify a customer and/or a courier associated with the order thatthe order is ready for pick-up. In various examples, the computingdevice can send the notification of order completion directly to thecourier associated with the order, informing the courier that the orderis ready for pick-up.

In various examples, the computing device can also receive anotification of an understock of a particular item from the kitchencomputing system. In such examples, the kitchen computing system candetermine that the completion of the order resulted in a decrease in astock of the particular item below a threshold level. In some examples,the computing device can determine an understock situation by comparingone or more items of the order to the notification of completion of theorder. In various examples, responsive to the notification of theunderstock and/or a determination of the understock situation, thecomputing device can automatically send an order for the particular itemto a supplier of menu items. In some examples, responsive to thenotification of the understock and/or a determination of the understocksituation, the computing device can automatically send a notification ofunavailability of the particular item to the delivery application. Insuch examples, the delivery application can modify a menu to remove theparticular item from a menu.

At 910, the computing device can process payment for the order. In someexamples, the computing device can process the payment based at least inpart on the notification of order completion. In various examples, thecomputing device can receive payment instrument information concurrentlywith the order. In such examples, the computing device can temporarilystore the payment instrument information until payment is processed. Insome examples, the computing device can access payment instrumentinformation stored in a customer profile corresponding to the customerassociated with the order.

FIG. 10 illustrates select components of an example service computingdevice 1000 configured with the dynamically modifiable user interfacesystem. The service computing device 1000 may be any suitable type ofcomputing device, e.g., mobile, semi-mobile, semi-stationary, orstationary.

Some examples of the service computing device 1000 may include tabletcomputing devices; smart phones and mobile communication devices;laptops, netbooks and other portable computers or semi-portablecomputers; desktop computing devices, terminal computing devices andother semi-stationary or stationary computing devices; dedicatedregister devices; wearable computing devices, or other body-mountedcomputing devices; or other computing devices capable of sendingcommunications and performing the functions according to the techniquesdescribed herein.

In the illustrated example, the service computing device 1000 includesat least one processor 1002, at least one memory 1004, a display 1006,one or more input/output (I/O) interfaces 1008, one or morecommunication interfaces 1010, one or more sensor(s) 1012, and at leastone location component 1014.

Each processor 1002 may itself comprise one or more processors orprocessing cores. For example, the processor 1002 can be implemented asone or more microprocessors, microcomputers, microcontrollers, digitalsignal processors, central processing units, state machines, logiccircuitries, and/or any devices that manipulate signals based onoperational instructions. In some cases, the processor 1002 may be oneor more hardware processors and/or logic circuits of any suitable typespecifically programmed or configured to execute the algorithms andprocesses described herein. The processor 1002 can be configured tofetch and execute computer-readable processor-executable instructionsstored in the memory 1004.

Depending on the configuration of the service computing device 1000, thememory 1004 may be an example of tangible non-transitory computerstorage media and may include volatile and nonvolatile memory and/orremovable and non-removable media implemented in any type of technologyfor storage of information such as computer-readableprocessor-executable instructions, data structures, program modules orother data. The memory 1004 may include, but is not limited to, RAM,ROM, EEPROM, flash memory, solid-state storage, magnetic disk storage,optical storage, and/or other computer-readable media technology.Further, in some cases, the service computing device 1000 may accessexternal storage, such as RAID storage systems, storage arrays, networkattached storage, storage area networks, cloud storage, or any othermedium that can be used to store information and that can be accessed bythe processor 1002 directly or through another computing device ornetwork. Accordingly, the memory 1004 may be computer storage media ableto store instructions, modules or components that may be executed by theprocessor 1002. Further, when mentioned, non-transitorycomputer-readable media excludes media such as energy, carrier signals,electromagnetic waves, and signals per se.

The memory 1004 may be used to store and maintain any number offunctional components that are executable by the processor 1002. In someimplementations, these functional components comprise instructions orprograms that are executable by the processor 1002 and that, whenexecuted, implement operational logic for performing the actions andservices attributed above to the service computing device 1000.Functional components of the service computing device 1000 stored in thememory 1004 may include a user interface modification framework 1016 anda payment processing framework 1018. The user interface modificationframework 1016 may be configured to analyze contextual data and modifyone or more icons of the user interface based on the contextual data, asdiscussed above with regard to FIGS. 1-7.

In various examples, the payment processing framework 1018 can beconfigured to communicate one or more orders to a base station computingdevice (e.g., a centralized computing device) for processing. In suchexamples, the base station computing device can process the payment viaa POS system service provider, a bank corresponding to the paymentinstrument, and/or another source. In some examples, the paymentprocessing framework 1018 can be configured to receive paymentinstrument information from the one or more sensor(s) 1012, such as apayment instrument reader. In still yet other examples, the paymentprocessing framework 1018 can be configured to access payment instrumentinformation for a particular customer stored in the customer profiles1026. In such an example, the service computing device 1000 canautomatically process payment based on an indication of ordercompletion.

Additional functional components may include an operating system 1020for controlling and managing various functions of the service computingdevice 1000 and for enabling basic user interactions with the servicecomputing device 1000 and/or a customer device. The memory 1004 may alsostore a data store 1022. The data store 1022 may be configured to storemerchant profile 1024, customer profiles 1026 and/or other informationpertaining to merchants and associated customers.

In addition, the memory 1004 may also store data, data structures andthe like, that are used by the functional components. Depending on thetype of the service computing device 1000, the memory 1004 may alsooptionally include other functional components and data, which mayinclude programs, drivers, etc., and the data used or generated by thefunctional components. Further, the service computing device 1000 mayinclude many other logical, programmatic and physical components, ofwhich those described are merely examples that are related to thediscussion herein.

The one or more communication interface(s) 1010 may include one or moreinterfaces and hardware components for facilitating communication withvarious other devices over a network or directly. For example,communication interface(s) 1010 may facilitate communication through oneor more of the Internet, cable networks, cellular networks, wirelessnetworks (e.g., Wi-Fi) and wired networks, as well as close-rangecommunications such as Bluetooth®, Bluetooth® low energy, and the like,as additionally enumerated elsewhere herein.

In various examples, the one or more communication interface(s) 1010 maywork in conjunction with the user interface modification framework. Forexample, the service computing device may receive a phone call via anetwork connection. Responsive to answering the phone call, the servicecomputing device 1000 may automatically modify a user interface todisplay icons corresponding to a menu. In various examples, the servicecomputing device 1000 may recognize a phone number corresponding to theincoming call, and may identify a particular customer profile associatedwith the customer stored in the customer profiles 1026 of the data store1022. In such examples, the service computing device 1000 may modify theicons based on one or more customer preferences and/or a transactionhistory of the customer stored in the particular customer profile.

FIG. 10 further illustrates that the service computing device 1000 mayinclude one or more displays 1006 mentioned above. Depending on the typeof computing device used as the service computing device 1000, the oneor more displays 1006 may employ any suitable display technology. Forexample, the one or more displays 1006 may be liquid crystal displays,plasma displays, light emitting diode displays, OLED (organiclight-emitting diode) displays, electronic paper displays, or any othersuitable type of displays able to present digital content thereon.However, implementations described herein are not limited to anyparticular display technology.

The I/O interfaces 1008, meanwhile, may include speakers, a microphone,a camera, and various user controls (e.g., buttons, a joystick, akeyboard, a keypad, etc.), a haptic output device, and so forth.

In various examples, the service computing device 1000 can include oneor more sensor(s) 1012. The one or more sensor(s) 1012 can include acamera, a laser scanner, a RADAR, a LIDAR, other proximity sensor, anaccelerometer, a gyroscope, a compass, a light sensor, a volume sensor,a payment instrument reader, or other sensor capable of capturing and/oranalyzing environmental factors.

The location component 1014 may include a GPS device able to indicatelocation information, or the location component 1014 may compriseanother other location-based sensor. Additionally, the service computingdevice 1000 may include various other components that are not shown,examples of which include removable storage, a power control unit, andso forth.

FIG. 11 illustrates select components of an example base stationcomputing device 1100 that a POS system may use as a centralizedcomputing device for the dynamically modifiable user interface systemand/or an order prioritization system. The base station computing device1100 may be any suitable type of computing device, e.g., mobile,semi-mobile, semi-stationary, or stationary.

Some examples of the base station computing device 1100 may includetablet computing devices; smart phones and mobile communication devices;laptops, netbooks and other portable computers or semi-portablecomputers; desktop computing devices, terminal computing devices andother semi-stationary or stationary computing devices; dedicatedregister devices; wearable computing devices, or other body-mountedcomputing devices; or other computing devices capable of sendingcommunications and performing the functions according to the techniquesdescribed herein.

In the illustrated example, the base station computing device 1100includes at least one processor 1102, at least one memory 1104, adisplay 1106, one or more input/output (I/O) interfaces 1108, one ormore communication interfaces 1110, one or more sensor(s) 1112 at leastone location component 1114.

Each processor 1102 may itself comprise one or more processors orprocessing cores. For example, the processor 1102 can be implemented asone or more microprocessors, microcomputers, microcontrollers, digitalsignal processors, central processing units, state machines, logiccircuitries, and/or any devices that manipulate signals based onoperational instructions. In some cases, the processor 1102 may be oneor more hardware processors and/or logic circuits of any suitable typespecifically programmed or configured to execute the algorithms andprocesses described herein. The processor 1102 can be configured tofetch and execute computer-readable processor-executable instructionsstored in the memory 1104.

Depending on the configuration of the base station computing device1100, the memory 1104 may be an example of tangible non-transitorycomputer storage media and may include volatile and nonvolatile memoryand/or removable and non-removable media implemented in any type oftechnology for storage of information such as computer-readableprocessor-executable instructions, data structures, program modules orother data. The memory 1104 may include, but is not limited to, RAM,ROM, EEPROM, flash memory, solid-state storage, magnetic disk storage,optical storage, and/or other computer-readable media technology.Further, in some cases, the base station computing device 1100 mayaccess external storage, such as RAID storage systems, storage arrays,network attached storage, storage area networks, cloud storage, or anyother medium that can be used to store information and that can beaccessed by the processor 1102 directly or through another computingdevice or network. Accordingly, the memory 1104 may be computer storagemedia able to store instructions, modules or components that may beexecuted by the processor 1102. Further, when mentioned, non-transitorycomputer-readable media excludes media such as energy, carrier signals,electromagnetic waves, and signals per se.

The memory 1104 may be used to store and maintain any number offunctional components that are executable by the processor 1102. In someimplementations, these functional components comprise instructions orprograms that are executable by the processor 1102 and that, whenexecuted, implement operational logic for performing the actions andservices attributed above to the base station computing device 1100.Functional components of the base station computing device 1100 storedin the memory 1104 may include user interface modification framework1116, such as user interface modification framework 1016, discussedabove, and an ordering framework 1118.

In various examples, the ordering framework 1118 can include an orderinghub for processing multiple orders. The multiple orders can be from thesingle computing device, such as a server computing device 1000, or frommultiple computing devices. In some examples, at least some of themultiple orders can be received from one or more delivery applications(e.g., applications configured to process delivery orders from one ormore customers).

In various examples, the ordering framework 1118 can receive an order,and determine a preparation time associated with the order. Thepreparation time can be based on a longest cooking time for the order, aquantity (e.g., number) of employees working in the kitchen, theparticular employees working in the kitchen, an upcoming employee shiftchange, how busy the dining room is, a quantity of orders currently in asequence queue, and other factors affecting a time it would take toprepare an order.

In some examples, the ordering framework 1118 can receive a plurality oforders, and can determine a sequence of the plurality of orders. Thesequence can be based on an arrival time of the order, the preparationtime associated with the order, location of the customer (e.g., at themerchant location or at a remote location), a pick-up time associatedwith the order (e.g., pre-determined pick-up time, delays due totraffic, weather, courier availability, etc.), and/or other factors.

In various examples, the ordering framework 1118 receive a plurality oforders, and can determine a sequence of sub-orders within the orders. Insuch examples, the items in the orders can be separated, and apreparation time of each item can be determined. Based on thepreparation time of each item, the items of the various orders can besequenced for efficiency. For example, two orders may be receivedsubstantially simultaneously, each of the orders including a salad and ahot entrée. The ordering framework 1118 can determine a preparation timefor the salads is 3 minutes and a preparation time for the hot entréesis 20 minutes. Based on the preparation times, the ordering framework1118 can sequence the items of the orders so that the salads andcorresponding hot entrées are ready at substantially the same time.

In some examples, the ordering framework 1118 can determine a longpreparation time and/or a delay for a particular item. In variousexamples, the ordering framework 1118 can communicate the information tothe various delivery applications and/or remote computing devices. Insuch examples, the delivery applications and/or remote computing devicescan de-emphasize the item, such as by modifying an icon corresponding tothe item on a menu, and/or provide a notification of delay regarding theitem and consequently a delay of an order including the item. In someexamples, the ordering framework 1118 can communicate the information tothe user interface modification framework 1116. Based on the informationabout the delay, the user interface modification framework 1116 cande-emphasize the item, such as by removing the icon associated therewithfrom a main page, making the icon smaller, and the like.

In various examples, the ordering framework 1118 and/or user interfacemodification framework 1116 can monitor merchant inventory. In suchexamples, the ordering framework 1118 and/or user interface modificationframework 1116 can update the merchant inventory (e.g., update a datastructure, database, etc. associated with the inventory) based onprocessed orders. The updates can be performed continuously (e.g., witheach order) and/or periodically (e.g., at a given time each day, everyhour, etc.).

In various examples, the ordering framework 1118 and/or user interfacemodification framework 1116 can monitor the merchant inventory, andcommunicate the merchant inventory to the service computing device. Insome examples, the ordering framework 1118 and/or user interfacemodification framework 1116 can push an update to the service computingdevice based on a determination that a particular item in the inventoryhas exceeded an overstock threshold level. The overstock threshold levelmay be set by the merchant, such as in merchant profile 1126, and/or bya POS system service provider. For example, the ordering framework 1118and/or user interface modification framework 1116 may determine that aparticular item is overstocked. Based on the overstock determination,the base station computing device 1100 may instruct the servicecomputing device to modify the user interface to emphasize theoverstocked item in an attempt to sell more of that item.

In some examples, the ordering framework 1118 and/or user interfacemodification framework 1116 can send a notification to the deliveryapplications and/or remote computing devices based on the overstockdetermination. The notification can include an instruction to emphasizethe item, a discount offered on the item, or other information toencourage the sale of the item.

In some examples, the ordering framework 1118 and/or user interfacemodification framework 1116 can push an inventory update (e.g., update aquantity of a particular item or group of items in the inventory,current quantities of inventory items in the data structure, database,etc.) to the service computing device based on a determination that aparticular item in the inventory has decreased below an understockthreshold level. The understock threshold level could be zero (0)remaining items, or a limited quantity of remaining items, as determinedby the merchant, such as in merchant profile 1126, and/or by a POSsystem service provider. For example, the ordering framework 1118 and/orthe user interface modification framework 1116 may determine that aparticular item is understocked (e.g., a limited amount or noneremaining). Based on the understock determination, the orderingframework 1118 and/or the user interface modification framework 1116send an instruction to the service computing device to de-emphasize theunderstocked item in an attempt to discourage the sale of the itemand/or attempt to cross-sell another item, such as by emphasizing acomparable item.

In some examples, the ordering framework 1118 and/or user interfacemodification framework 1116 can send a notification to the deliveryapplications and/or remote computing devices based on the understockdetermination. The notification can include an instruction tode-emphasize the item, remove the item from the menu, attempt tocross-sell another item, such as by emphasizing a comparable item, orother instruction and/or information to discourage the sale of the item.

In various examples, the memory 1104 can include a payment processingframework 1120. In such examples, the payment processing framework 1120can be configured to receive payment information from a servicecomputing device, delivery application, and/or other remote computingdevices. The payment processing framework 1120 can process the paymentvia a POS system service provider, a bank corresponding to the paymentinstrument, and/or another source. In some examples, the paymentprocessing framework 1120 can be configured to receive paymentinstrument information from the one or more sensor(s) 1112, such as apayment instrument reader. In still yet other examples, the paymentprocessing framework 1120 can be configured to access payment instrumentinformation for a particular customer stored in the customer profiles1126. In such an example, the base station computing device 1100 canautomatically process payment based on an indication of ordercompletion.

Additional functional components may include an operating system 1122for controlling and managing various functions of the base stationcomputing device 1100 and for enabling basic user interactions with thebase station computing device 1100 and/or a customer device. The memory1104 may also store a data store 1124. The data store 1124 may beconfigured to store a merchant profile 1126, customer profiles 1128and/or other information pertaining to the merchant and associatedcustomers.

In addition, the memory 1104 may also store data, data structures andthe like, that are used by the functional components. Depending on thetype of the base station computing device 1100, the memory 1104 may alsooptionally include other functional components and data, which mayinclude programs, drivers, etc., and the data used or generated by thefunctional components. Further, the base station computing device 1100may include many other logical, programmatic and physical components, ofwhich those described are merely examples that are related to thediscussion herein.

The one or more communication interface(s) 1110 may include one or moreinterfaces and hardware components for facilitating communication withvarious other devices over a network or directly. For example,communication interface(s) 1110 may facilitate communication through oneor more of the Internet, cable networks, cellular networks, wirelessnetworks (e.g., Wi-Fi) and wired networks, as well as close-rangecommunications such as Bluetooth®, Bluetooth® low energy, and the like,as additionally enumerated elsewhere herein.

FIG. 11 further illustrates that the base station computing device 1100may include one or more displays 1106 mentioned above. Depending on thetype of computing device used as the base station computing device 1100,the one or more displays 1106 may employ any suitable displaytechnology. For example, the one or more displays 1106 may be liquidcrystal displays, plasma displays, light emitting diode displays, OLED(organic light-emitting diode) displays, electronic paper displays, orany other suitable type of displays able to present digital contentthereon. However, implementations described herein are not limited toany particular display technology.

The I/O interfaces 1108, meanwhile, may include speakers, a microphone,a camera, and various user controls (e.g., buttons, a joystick, akeyboard, a keypad, etc.), a haptic output device, and so forth.

In various examples, the base station computing device 1100 can includeone or more sensor(s) 1112. The one or more sensor(s) 1112 can include acamera, a laser scanner, a RADAR, a LIDAR, other proximity sensor, anaccelerometer, a gyroscope, a compass, a light sensor, a volume sensor,or other sensor capable of capturing and/or analyzing environmentalfactors.

The location component 1114 may include a GPS device able to indicatelocation information, or the location component 1114 may compriseanother other location-based sensor. Additionally, the base stationcomputing device 1100 may include various other components that are notshown, examples of which include removable storage, a power controlunit, and so forth.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described. Rather,the specific features and acts are disclosed as example forms ofimplementing the claims.

What is claimed is:
 1. A system comprising: one or more processors; oneor more non-transitory computer-readable media storing instructionsexecutable by the one or more processors, wherein the instructionsprogram the one or more processors to perform acts comprising:receiving, by a computing device associated with a merchant, a firstorder of a plurality of orders from a first delivery application of aplurality of delivery applications, the first order comprising a firstset of menu items and first payment information; receiving, by thecomputing device associated with the merchant, a second order of theplurality of orders from a second delivery application of the pluralityof delivery applications, the second order comprising a second set ofmenu items and second payment information; determining a first timeassociated with the first order and a second time associated with thesecond order, wherein the first time and the second time arerespectively based at least in part on a first preparation timeassociated with the first set of menu items and a second preparationtime associated with the second set of menu items; sending a firstnotification to the first delivery application and a second notificationto the second delivery application, the first notification comprising afirst estimated time for a delivery pick-up corresponding to the firstorder and the second notification comprising a second estimated time fora delivery pick-up corresponding to the second order, wherein the firstestimated time is based at least in part on the first time and secondestimated time is based at least in part on the second time; generatinga sequenced list of orders based at least in part on the first time andthe second time; sending the sequenced list of orders to a kitchendisplay system; receiving, from the kitchen display system, a firstnotification of completion of the first order; processing payment forthe first order based at least in part on the first notification ofcompletion and the first payment information; receiving, from thekitchen computing system, a second notification of completion of thesecond order; and processing payment for the second order based at leastin part on the second notification of completion and the second paymentinformation.
 2. The system as claim 1 recites, the acts furthercomprising receiving, from the kitchen display system, an indicationthat a quantity of a particular menu item has been decreased below athreshold quantity; and responsive to receiving the indication,automatically sending, to the plurality of delivery applications, anotification that the particular menu item is not available.
 3. Thesystem as claim 1 recites, the acts further comprising: receiving, fromthe kitchen display system, an indication that a quantity of aparticular menu item has decreased below a threshold quantity; andresponsive to receiving the indication, automatically sending, to asupplier of menu items, an order for the particular menu item.
 4. Thesystem as claim 1 recites, the acts further comprising: receiving, fromthe kitchen display system, an indication that a prep time associatedwith the first order exceeds the first time; determining an updatedfirst estimated time for the delivery pick-up; and sending, to the firstdelivery application, a notification of the updated first estimatedtime.
 5. The system as claim 1 recites, the acts further comprising:receiving, from the kitchen display system, an indication that aquantity of employees in the kitchen is below a pre-determined thresholdquantity; and sending, to a mobile device of a manager associated withthe merchant, a notification that the kitchen is understaffed.
 6. Amethod comprising: receiving a plurality of orders for items offered bya merchant from a plurality of delivery applications independent of themerchant; determining a time associated with each order of the pluralityof orders; sending each order of the plurality of orders to a kitchendisplay system; receiving, from the kitchen display system, anotification of completion of an order; and based at least in part onthe notification, processing a payment for the order.
 7. The method asclaim 6 recites, further comprising: determining one or more itemsassociated with each order of the plurality of orders; determining atime associated with each item of the one or more items; and generatinga sequenced list of the items associated with the plurality of ordersbased at least in part on respective times associated with respectiveitems of the one or more items, wherein the sending each order of theplurality of orders to the computing system associated with the kitchencomprises sending the sequenced list of the items.
 8. The method asclaim 6 recites, further comprising: determining one or more itemsassociated with each order of the plurality of orders; updating a datastructure corresponding to an inventory of the merchant based at leastin part on the one or more items; determining a quantity of an item ofthe inventory is below a threshold minimum quantity; and sending anotification to the plurality of delivery applications that the item isno longer available.
 9. The method as claim 6 recites, furthercomprising: determining one or more items associated with each order ofthe plurality of orders; updating a data structure associated with aninventory of the merchant based at least in part on the one or moreitems; determining a quantity of an item of the inventory is below athreshold minimum quantity; and sending, to an item supplier, an orderfor the item.
 10. The method as claim 6 recites, further comprising:determining an upcoming shift change in the kitchen, wherein theupcoming shift change comprises an increased quantity of employeesworking in the kitchen; and modifying the time associated with eachorder based at least in part on the upcoming shift change.
 11. Themethod as claim 6 recites, further comprising: identifying a customerassociated with the order; and determining payment instrumentinformation associated with the customer, wherein the payment instrumentinformation is stored in a customer profile associated with thecustomer, wherein processing the payment for the order comprisesprocessing the payment instrument information stored in the customerprofile.
 12. The method as claim 6 recites, further comprising:receiving, from the kitchen display system, an indication of delay ofone or more of the plurality of orders; determining an updated timeassociated with the one or more orders; and sending, to respectivedelivery applications of the one or more orders, a notification of theupdated time.
 13. The method as claim 6 recites, receiving one or moreorders from a service computing device; determining a time associatedwith each order of the one or more orders; generating a sequenced listof the plurality of orders from the plurality of delivery applicationsand the one or more orders from the service computing device; andsending the sequenced list to the kitchen display system.
 14. The methodas claim 6 recites, wherein the time associated with each order is basedon one or more of: a preparation for each order; a cooking time for eachorder; weather; a quantity of employees working in the kitchen; traffic;or courier availability.
 15. A computing device comprising: one or moreprocessors; one or more non-transitory computer-readable media storinginstructions executable by the one or more processors, wherein theinstructions program the one or more processors to perform actscomprising: receiving a plurality of orders for items offered by amerchant from a plurality of delivery applications independent of themerchant; determining a preparation time associated with each order ofthe plurality of orders; sequencing each order of the plurality oforders based on the determined preparation time; sending each order ofthe plurality of orders to a kitchen display system; receiving, from thekitchen display system, a notification of completion of an order; andbased at least in part on the notification, processing a payment for theorder.
 16. The computing device as claim 15 recites, the acts furthercomprising, determining one or more items associated with each order ofthe plurality of orders; updating a data structure corresponding to aninventory of the merchant based at least in part on the one or moreitems; determining a quantity of an item of the inventory is below athreshold minimum quantity; and sending, to an item supplier, an orderfor the item or sending, to the plurality of delivery applications, anotification that the item is no longer available.
 17. The computingdevice as claim 15 recites, the acts further comprising: receiving, fromthe kitchen display system, an indication of delay of one or more of theplurality of orders; determining an updated time associated with eachorder of the one or more orders; and sending, to respective deliveryapplications, a notification of the respective updated time.
 18. Thecomputing device as claim 15 recites, the acts further comprising:receiving, from the kitchen display system, an indication that aquantity of employees in the kitchen is below a pre-determined thresholdquantity; and sending, to a mobile device of a manager associated withthe merchant, a notification that the kitchen is understaffed.
 19. Thecomputing device as claim 15 recites, the acts further comprising:identifying a customer associated with the order; and determiningpayment instrument information associated with the customer, wherein thepayment instrument information is stored in a customer profileassociated with the customer, wherein processing the payment for theorder comprises processing the payment instrument information stored inthe customer profile.
 20. The computing as claim 15 recites, wherein thetime associated with each order is based on one or more of: apreparation for each order; a cooking time for each order; weather; aquantity of employees working in the kitchen; traffic; or courieravailability.